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Depth prediction of non-air interface defect using pulsed thermography
Abstract
Prediction of defect depth has been an important quantitative application of pulsed thermography and several methods have been reported in the literature. However, all those methods consider only the situation where the interface between sample and defect is sample–air. In this paper, using an analysis based on a theoretical one-dimensional solution of pulsed thermography, we analyzed the depth predicting principle and procedure of four representative methods for non-air interface situation. The numerical simulations were compared with experimental results of one steel sample milled with eight flat-bottom holes, and each hole was filled with different materials to simulate different non-air interfaces. The comparison shows that the peak contrast time method is badly affected by the defect interface; however, other three methods are not affected.
... Defect depth and residual thickness are two parameters that need to be resolved to characterise a defect. Many reports describe a positive relationship between defect depth, residual thickness, and the specific characteristic time of the inspected surface; however, most of these reports only consider defects at the sample-air interface [5,[11][12][13][14][15][16][17][18]. Externally corroded walls in buried pipes are not usually located at the sample-air interface. ...
... In this case, a sample-sand interface would be a more suitable model. Zeng et al. [14] investigated the effect of non-air interfaces in the estimation of residual thickness. Using the peak contrast time (PCT) method, they showed that the interface material (water, wax or oil) influences the measurement. ...
... Therefore, different defect interfaces theoretically result in different surface temperatures. However, the effect of defect interfaces had not been explored in-depth in the past and even for study that explored the effect of defect interfaces, their study focuses on interface of water and oil with uniform defect size and very small residual thickness [14]. Therefore, to fit in the case of underground metallic utilities, experiment is needed. ...
This study characterized the in-pipe thermal signature of external pipewall thinning in steel pipes, a common problem that is caused by external corrosion in hostile underground environment. A model system was prepared to imitate the underground environment by milling several holes of various sizes and residual thicknesses into a mild steel plate. Wall thinning was investigated using active infrared thermography. The non-defective side of the steel plate was heated to 27.4 °C through the application of a thermal energy pulse while the ambient temperature was 22°C. Thermograms were captured inside the pipe at a frequency of 0.02 seconds for 5 min. The images of the thinned surface were processed in two steps. First, the peak contrast time algorithm was used to estimate the residual thickness. Second, Gaussian adaptive thresholding was used to estimate the size of the holes. The maximum observable defects had a diameter of 5 mm and a residual thickness of 3 mm. The type of defect interface (steel–sand or steel–air) had no significant effect on the estimation of residual thickness or size. This study developed a rapid approach in classifying defect's residual thickness by only utilizing two well-known parameters from infrared images – defect's peak thermal contrast and estimated area. Thus, the feasibility of non-destructive, in-pipe, quantitative IR thermographic analysis of buried metal pipelines is demonstrated.
... Through the thermogram sequence recorded by an infrared camera, the dynamic change of the surface temperature distribution can be obtained, which conveys information about internal defects in the spec- imen. Based on the type of photothermal excitation source, transient thermography can be divided into pulse thermography (PT) and step heating thermography (SHT) [25], [26]. With the advantages of fast, large single detection area, quantitative detection, and visualization, transient thermography has been successfully applied in composites detection. ...
... In the experiment of changing the irradiance, the sample was tested at the distance of 4 m by SHT, and the focal length of the camera was 100 mm, while the heating time was changed to 15,20,25,30, and 35 s, respectively. Fig. 8 shows the detection results after feature extraction, and Fig. 9(a) shows the change curve of mDL in the experiment. ...
... In engineering, the detection effect is often improved by extending the heating time. For sample A, eight experiments were carried out with 1-m intervals between 3 and 10 m with the heating times of 17,20,25,30,35,40,45, and 50 s, respectively. For sample B, seven experiments were carried out from 4 to 10 m at 1-m intervals, with the heating time settings kept the same as for sample A. The PPM varied with distance as 2222, 1667, 1333, 1111, 952, 833, 741, and 667, respectively. ...
Composite materials are commonly used in industrial systems for their superior physical and chemical properties. Due to the necessity for safety distance in industrial systems, non-destructive testing (NDT) for composites at long distances provides an important guarantee for prompt detection of internal equipment failures. The existing long-distance inspection methods are mostly passive NDT techniques. In this paper, a long-distance NDT method based on transient thermography is proposed. A theoretical model is established that integrates the transient thermography approach with the thermographic distance effect, providing the theoretical foundation for research based on distance detection effects. Different thermal wave features are extracted based on thermal physical parameters in the time and frequency domains, and the detection effect is compared based on different feature images. By conducting experiments on SIR–GFE bonded plate with artificially simulated internal defects, the effectiveness of both pulse thermography (PT) and step heating thermography (SHT) in long-distance inspection was compared, in which the SHT method was superior. The detection effect of feature images at different distances are compared using the SHT technique, the model’s validity is tested, and the law of the function of distance in transient thermal imaging detection is derived. This work introduces the influence of distance in transient thermography for the first time, and it is hoped that this research can effectively guide and improve real industrial inspection.
... As for coating thickness measurement with infrared thermography, Zeng et al. analyzed the depth predicting principle and procedure of four representative methods for the non-air interface situation, and compared with experimental results of one steel sample machined with eight flat-bottom holes, based on a theoretical one-dimensional solution of pulsed thermography [8]. Zhang et al. proposed a relationship between coatings thickness and phase of lock-in thermography and realized fast inspection of coating thickness with high inspection accuracy [9]. ...
... In addition, long pulse thermography does not require accurate synchronization of the thermal excitation with the IR acquisition system [19,20]. Previous investigations have demonstrated that some different types of specific characteristic time, such as the peak contrast time, the peak slope time and the peak second-derivative time of logarithmic temperature, are known to be linearly proportional to the square of thickness based on PT [7,8,15]. However, whether the above relationships still exist for thickness measurement based on LPT remains unknown. ...
... It demonstrates the time at the minimum of the 2nd derivative is linear changing with L 2 /α, with the R-square value (R 2 = 0.99998) close to unity, which indicates the coating thickness can be determined based on the time at the minimum of the 2nd derivative. The linear relationship between a specific characteristic time and the parameter L 2 /α was also observed in pulsed thermography [7,8]. ...
Non-destructive detection of coating thickness is important after coating deposition and during service. The present work is to establish a measurement method for fast inspection, large area detection of coating thickness with an active long pulse thermography. The measurement method was theoretically analyzed based on the equation of 1D heat transfer in the depth direction, accordingly coating thickness can be quantitively evaluated by recording the temperature decay curve in the cooling stage and computing the time at the minimum of its 2nd derivative. Then, the proposed method was experimentally validated by uniform coating specimen with different thicknesses. Furthermore, the thickness measurement method was successfully applied to measure thickness of an uneven coating specimen within a relative error of 5% with sufficient sampling rate. Finally, some key techniques were discussed for accurate measurements including thermal excitation, sampling rate of thermography, thickness ratio of coating and substrate, etc. The results verify that active long pulse thermography is a powerful tool for non-contact and full-field measurement of coating thickness with merits of safe and easy to implement.
... This approach is compared with two conventional thermographic approaches, viz. peak logarithmic second derivative and frame subtraction [9][10][11]. The theoretical underpinning of these approaches is summarised in Section 3. The focus for the present paper is an experimental evaluation of these approaches for synthetic defects in a membrane that is in contact with either water (simulating liquid sewage), or garden soil (simulating scum), or air (simulating pockets of biogas). ...
... Data analysis for pulsed thermography generally relies on tracking the surface temperature difference between a potentially defective location and a reference location that is presumed to be defect-free [9][10][11]. This temperature contrast curve typically shows a maximum at a particular time instant, known as the peak contrast time (PCT), that is approximately proportional to the square of the defect depth beneath the surface. ...
... This method was implemented with the first frame (corresponding to in Equation (11)) taken at the start of the transient event, the final frame at the end of the transient event at approximately 12:27:00, and with a time step of Δ = 10 s. Most of the subsurface defects can be identified (specifically defects 2, 3, 5, 6 in the soil region and defects 8,9,11,12 in the air region), and the colour contrast can be considered to provide an indication of the defect depth, in view of the observation that the strength of contrast increases with decreasing membrane thickness. However, the contrast between substrates is reduced due to the altered threshold that has been employed in this image display to highlight the defects. ...
High-density polyethylene geomembranes are employed as covers for the sewage treatment lagoons at Melbourne Water Corporation’s Western Treatment Plant, to harvest the biogas produced during anaerobic degradation, which is then used to generate electricity. Due to its size, inspecting the cover for defects, particularly subsurface defects, can be challenging, as well as the potential for the underside of the membrane to come into contact with different substrates, viz. liquid sewage, scum (consolidated solid matter), and biogas. This paper presents the application of a novel quasi-active thermography inspection method for subsurface defect detection in the geomembrane. The proposed approach utilises ambient sunlight as the input thermal energy and cloud shading as the trigger for thermal transients. Outdoor laboratory-scale experiments were conducted to study the proposed inspection technique. A pyranometer was used to measure the intensity of solar radiation, and an infrared thermal camera was used to measure the surface temperature of the geomembrane. The measured temperature profile was analysed using three different algorithms for thermal transient analysis, based on (i) the cooling constant from Newton’s law of cooling, (ii) the peak value of the logarithmic second derivative, and (iii) a frame subtraction method. The outcomes from each algorithm were examined and compared. The results show that, while each algorithm has some limitations, when used in combination the three algorithms could be used to distinguish between different substrates and to determine the presence of subsurface defects.
... There are plentiful publications devoted to quantitative depth evaluation [12][13][14][15][16][17]. Many studies establish the proportionality between squared defect depths and the corresponding specific characteristic time (SCT) of heat conduction. ...
... This suggests that the real defects, such as inclusions, delaminations, cracks etc., should be characterized by varying R values. A weak dependence of SCT on R was demonstrated in [17,23] without taking into account defect finite dimensions. In fact, the model suggested in [22] shows that R values affect both the amplitude and time of peak contrasts, as well as the shape of temperature evolution curves and, correspondingly, the values of other proposed SCTs. ...
... Equation (3) was used for determining detection limits but assuming R = 1 and n = 1, which might not be true in practice [23]. According to [17,23], the analysis of Equation (3) shows that R values mainly affect maximal temperature signals (peak contrasts) but not optimal observation times (peak contrast times tpeak). However, it follows from Equation (4) that a change in the coefficient R also shifts a position of the peak contrast time if the finite size of defects is taken into account. ...
This study is focused on the quantitative estimation of defect depth by applying pulsed thermal nondestructive testing. The majority of known defect characterization techniques are based on 1D heat conduction solutions, thus being inappropriate for evaluating defects with low aspect ratios. A novel method for estimating defect depth is proposed by taking into account the phenomenon of 3D heat diffusion, finite lateral size of defects and the thermal reflection coefficient at the boundary between a host material and defects. The method is based on the combination of a known analytical model and a non-linear fitting (NLF) procedure. The algorithm was verified both numerically and experimentally on 3D-printed polylactic acid plastic samples. The accuracy of depth prediction using the proposed method was compared with the reference characterization technique based on thermographic signal reconstruction to demonstrate the efficiency of the proposed NLF method.
... Thermography is generally classified into (1) active thermography and (2) passive thermography [12][13][14]. Active thermography [15][16][17][18] requires the monitored object to be subjected to some external source of thermal energy that acts as a stimulus. The input heat energy will penetrate the test specimens and the regions with different properties, such as defects in specimens, will then become obvious in thermal images due to the different responses to the transient heat flow through the object [12]. ...
... They used a commercial PT system to trigger the temperature gradients on specimens and the damaged regions showed the same profiles as in ultrasonic inspections. Zeng et al. [18] conducted PT experiments to predict the depth of defects where the defects were in contact with objects in a different phase (water, oil and wax). Breitenstein et al. [19] inspected the defects of silicon solar cells using lock-in thermography. ...
... The cover material acts like a reflective layer which partially reflects the heat back to the soil and air (absorb from soil and air and re-emitted back to soil and air). The thermal wave reflection coefficient [18] of air interface and soil interface is different, leading to efficiency of heat exchange different between the air/geomembrane medium and the soil/geomembrane medium. ...
Melbourne Water Corporation has two large anaerobic lagoons at the Western Treatment Plant (WTP), Werribee, Victoria, Australia. The lagoons are covered using numerous sheets of high-density polyethylene (HDPE) geomembranes to prevent the emission of odorous gases and to harness biogas as a source of renewable energy. Some of the content of raw sewage can accumulate and form into a solid mass (called "scum"). The development of a large body of solid scum that rises to the surface of the lagoon (called "scumbergs") deforms the covers and may affect its structural integrity. Currently, there is no method able to effectively "see-through" the opaque covers to define the spread of the scum underneath the cover. Hence, this paper investigates a new quasi-active thermal imaging method that uses ambient solar radiation to determine the extent of the solid matter under the geomembrane. This method was devised by using infrared thermography and a pyranometer to constantly monitor the transient temperature response of the HDPE geomembrane using the time varying ambient solar radiation. Newton's cooling law is implemented to define the resultant cooling constants. The results of laboratory-scale tests demonstrate the capability of the quasi-active thermography to identify the presence and the extent of solid matter under the cover. This paper demonstrates, experimentally, the importance of measuring the surface temperature of the cover and solar intensity profiles to obtain the cooling process when during variations in solar intensity during normal sunrise, sunset, daily transitioning from morning-afternoon-evening and cloud cover events. The timescale associated with these events are different and the results show that these daily transient temperature cycles of the geomembranes can be used to detect the extent of the accumulation of solid matter underneath the geomembrane. The conclusions from this work will be further developed for field trials to practically monitor the growth in the extent of the scum under the floating covers in WTP with the ambient solar energy.
... Chen et al. [30] used the non-convex empirical Bayes method to model low rank tensor. In addition, based on the application in flow data, stochastic [31], incremental tensor [32] and recursive [33] tensor decomposition algorithms have also been proposed. In the field of NDT applications, Gao et al. [34] used the CP decomposition to model thermography spatial-transient stage and material property characterization. ...
... In order to illustrate the difficulty and challenge of our special defect task detection in the field of non-destructive testing, we first show the processing results of the traditional feature extraction algorithm PCA [42], sparse PCA (SPCA) [43], the latest online sparse matrix algorithm SGSM-BS [24] and incremental tensor decomposition IMTSL [32] algorithm in figure 7. More detailed experimental results are shown in the electronic supplementary material. ...
... In recent years, several methods estimate the defect depth by using a characteristic time [30,31]. The first proposed and the most commonly used method utilizes the time point when the maximum thermal contrast between a defective and a sound reference point occurs, known as Peak Contrast Time [32][33][34]. It was found that the peak contrast time is approximately proportional to the square of the defect depth [35]. Krapez et al. [36] proposed the time point on the temperature-time curve is the moment when the temperature signal above the defects diverges from the reference signal. ...
With the advancement of electromagnetic induction thermography and imaging technology in non-destructive testing field, this system has significantly benefitted modern industries in fast and contactless defects detection. However, due to the limitations of front-end hardware experimental equipment and the complicated test pieces, these have brought forth new challenges to the detection process. Making use of the spatio-temporal video data captured by the thermal imaging device and linking it with advanced video processing algorithm to defects detection has become a necessary alternative way to solve these detection challenges. The extremely weak and sparse defect signal is buried in complex background with the presence of strong noise in the real experimental scene has prevented progress to be made in defects detection. In this paper, we propose a novel hierarchical low-rank and sparse tensor decomposition method to mine anomalous patterns in the induction thermography stream for defects detection. The proposed algorithm offers advantages not only in suppressing the interference of strong background and sharpens the visual features of defects, but also overcoming the problems of over- and under-sparseness suffered by similar state-of-the-art algorithms. Real-time natural defect detection experiments have been conducted to verify that the proposed algorithm is more efficient and accurate than existing algorithms in terms of visual presentations and evaluation criteria.
This article is part of the theme issue ‘Advanced electromagnetic non-destructive evaluation and smart monitoring’.
... La profondeur des défauts peut être quantifiée par le biais de cette perturbation. Pour cela, il existe de nombreuses méthodes qui ont été proposées, comme : Peak Contrast Time (PCT) ou Peak Slope Time (PST) et Logarithmic Peak-Derivative (LSPD) [12]. Mais aussi des approches de type : Absolute Peak Slope Time (APST) [13], Early Detection Approch (EDA) [14], Least-Squares Fitting (LSFM) [15] et Thermal Signal Reconstruction (TSR) [16]. ...
... Il a été démontré que la méthode est très robuste et finalement très peu sensible à ces sources d'erreurs. En effet, l'erreur obtenue sur l'estimation des diffusivités thermiques est de l'ordre de 1% quand le bruit de mesure avoisine les 100% du signal « moyen» (figure [3][4][5][6][7][8][9][10][11][12][13]. De même, il faut savoir qu'expérimentalement, il est difficile d'obtenir une source thermique complètement ponctuelle. ...
... Dans cette partie l'objectif est d'utiliser l'outil développé à la mesure de champs de diffusivités thermiques en milieu hétérogène anisotrope. Un échantillon comprenant différents types de matériaux a été assemblé (figure [5][6][7][8][9][10][11][12]. Cet échantillon est composé de quatre sous matériaux aux propriétés thermiques très différentes : (a), un composite carbone / époxy dont les fibres sont tressées, (b), un plexiglas homogène et isotrope peint d'une fine couche (200 µm) de peinture noire, (c), un échantillon hétérogène de pin maritime dont les fibres sont orientées selon x et (d), un composite homogène carbone / époxy dont les fibres sont orientées selon y. spatiale d'un pixel de la caméra infrarouge est fixée à 250 µm (avec une incertitude de ± 4 µm) par pixel, (ii), la fréquence d'acquisition de la caméra est fixée à 200 Hz, (iii), le temps d'intégration est pris égal à 500 µs et (iv) l'acquisition est réalisée sur une durée de t = 7 s, ce qui représente 1500 images. ...
De nos jours, les matériaux composites sont très largement utilisés dans l’industrie aéronautique et aérospatiale car ils ont de très bonnes tenues mécaniques, mais ces matériaux comportent de fortes hétérogénéités dues aux fibres et aux liants qui les constituent. Ainsi, depuis de nombreuses années, l’équipe TIFC «Thermal Imaging Fields and Characterization » du département TREFLE de l’institut I2M développe des méthodes de mesure des propriétés thermophysiques de matériaux hétérogènes dans le plan ou dans l’épaisseur. Ces méthodes sont très variées du point de vue des méthodes inverses (transformée intégrale, double décomposition en valeurs singulières, …) ou expérimentale (Flash, diode laser, …). Le faible coût des diodes lasers et des systèmes de déplacement de miroirs galvanométriques ont permis de développer un système complet de scanner optique laser, monté sur un banc de mesure. Il permet de revisiter les différents types de sollicitations thermiques et de réaliser une infinité de combinaisons spatiotemporelles d’excitations thermiques par méthode laser. Ceci est une des principales originalités de ce travail. De nouvelles méthodes inverses basées sur la réponse thermique au point source impulsionnel et sur la séparabilité des champs de température ont été proposées. Ces méthodes ont permis d’estimer le tenseur de diffusivité thermique selon les axes principaux d’anisotropie, mais aussi hors des axes du repère de l’image, où il est possible de déterminer l’orientation des axes d’anisotropie, lorsque le transfert de chaleur s’effectue hors des axes du repère de l’image. Ces méthodes ont permis d’obtenir des résultats intéressants comptetenu de leur simplicité. De plus, elles ont permis d’obtenir des cartographies de diffusivités thermiques dans le plan car, comparées aux autres méthodes, elles permettent d’obtenir des estimations du tenseur de diffusivité thermique localement grâce à l’obtention d’une cartographie de flux thermique surfacique via le scanner optique laser.
... where ∆ ( ) T t is the temperature variation of the surface at time t, Q is the pulse energy J, ρ is the material density (kg/m 3 ), c is the heat capacity (J/K kg), k is the thermal conductivity of the material (W/(K m)), and α is the thermal diffusivity (m /s 2 ). In order to obtain a specific characteristic time without a reference curve, Zeng et al. [19,22] proposed to first multiply both sides of Eq. (1) with t , and define a new time-dependent function ( ) f t as: ...
... The reconstructed ( ) ∆T t and ( ) f t can then be produced using Eq. (22), and they are plotted by the dash red curve in Fig. 2(a) and (b) respectively. Inspection shows that the reconstructed signals fit the observed signals very well, which is also confirmed by inspection of the fitting error between ( ) f t and ( ) f t , shown in Fig. 2(c). ...
... The value of N was automatically selected as 8 for all three pixels. Assuming the thermal decay of this experiment follows Eq. (22), the value of SNR for each pixel was calculated and results are 30. 13 dB, 30. ...
This paper introduces a new method to improve the reliability and confidence level of defect depth measurement based on pulsed thermographic inspection by addressing the over-fitting problem. Different with existing methods using a fixed model structure for all pixels, the proposed method adaptively detects the optimal model structure for each pixel thus targeting to achieve better model fitting while using less model terms. Results from numerical simulations and real experiments suggest that (a) the new method is able to measure defect depth more accurately without a pre-set model structure (error is usually within 1% when SNR 4 32 dB) in comparison with existing methods, (b) the number of model terms should be 8 for signals with SNR∈ ] ⎡ ⎣ dB dB 30 , 40 , 8–10 for SNR 4 40 dB and 5–8 for SNR o 30 dB, and (c) a data length with at least 100 data points and 2–3 times of the characteristic time usually produces the best results.
... Based on a theoretical one-dimensional solution of pulsed thermography, [59] analyzed the depth predicting principle and procedure of four representative methods for the non-air interface situation, and compared with experimental results of one machined steel sample with eight flatbottom holes. The results indicate that Peak slope time (PST), Absolute peak slope time (APST) and Logarithmic peak second-derivative (LPSD) methods can give accurate defect depth for all kinds of sample-defect interface. ...
... Based on a theoretical one-dimensional solution of pulsed thermography, [59] analyzed the depth predicting principle and procedure of four representative methods for the non-air interface situation, and compared with experimental results of one machined steel sample with eight flat-bottom holes. ...
... The results indicate that Peak slope time (PST), Absolute peak slope time (APST) and Logarithmic peak second-derivative (LPSD) methods can give accurate defect depth for all kinds of sample-defect interface. However, the Peak contrast time (PCT) method is easily affected by defect size, sample-defect interface [59]. On the other hand Zeng et al. [60] propose a new method for defect depth prediction. ...
Active thermography methods enable structural investigations of reinforced concrete elements taking into account many different testing problems. The goal of this review is to provide an overview on the state-of-the-art regarding the use of active infrared thermography (IRT) for detection and characterization of defects in reinforced concrete. The paper will provide the physical background, equipment being used, as well as post-processing methods that are used to analyse sequences of thermograms. This work also presents the fields of applicability of IRT with a focus on the aspects related to reinforced concrete structures, as well as the advantages, limitations and potential sources of errors of IRT employment. Additionally previous non-destructive testing (NDT) studies that employed thermography techniques with natural excitation are briefly presented. A review of the future trends of thermal imaging are also included in this work. It can be concluded that while IRT is a useful tool for the characterisation of defects in the building sector, there is great prospect for the development of more advanced, effective and accurate approaches that will employ a combination of thermography approaches.
... Pulsed (PT) [7][8][9][10][11][12] and lock-in (LT) [13][14][15][16][17][18][19][20][21][22] thermography are the techniques used in the last years for defect depth, thickness or more in general defect/damage measurement. The potential and limits of the flash thermography technique have been investigated by Shepard et al. [7,8]. ...
... In particular, the capability of the TSR ® algorithm in evaluating the thickness of Thermal Barrier Coatings has been demonstrated. Zeng et al. [9] investigated the defect depth by using a theoretical one-dimensional solution of pulsed thermography and comparing four representative methods for the non-air interface situation. ...
Many structural components made of composite materials need an accurate thickness control during fabrication and/or maintenance. In this regard, various non-destructive techniques can be used for the online measuring of thickness of large components such as wings and fuselage in the aerospace industry. In this work, the capabilities of lock-in thermography technique in thickness measurement of glass fiber reinforced plastic material were investigated and a correct procedure has been proposed to ensure the best measurement accuracy. An analytical approach and several tests were carried out on a sample specimen with the aim to study the main test parameters. Finally, the limits of technique have been discussed.
... PCT measures the peak time of the temperature contrast between the considered point and the reference point, and PST detects the peak time of the first derivative of temperature contrast. Both PCT and PST are approximately proportional to the square of the defect depth, whereas the proportionality coefficient of the PCT method depends on the size of the defect, but the proportionality coefficient of the PST method does not depend on the size of the defect [39]. In general, the reference point is manually chosen from the sound area. ...
... The LSF method uses a curve fitting technique to fit the temperature decay curve based on a theoretical heat transfer model to determine the defect depth directly. This method is less susceptible to noise but it presumes that the thermal wave reflection coefficient (ܴ) is 1, which is not true for most real situations [39]. Such an assumption can affect the accuracy of the estimated parameters of the heat transfer model using optimisation techniques. ...
Thermography is a promising method for detecting subsurface defects, but accurate measurement of defect depth is still a big challenge because thermographic signals are typically corrupted by imaging noise and affected by 3D heat conduction. Existing methods based on numerical models are susceptible to signal noise and methods based on analytical models require rigorous assumptions that usually cannot be satisfied in practical applications. This paper presents a new method to improve the measurement accuracy of subsurface defect depth through determining the thermal wave reflection coefficient directly from observed data that is usually assumed to be pre-known. This target is achieved through introducing a new heat transfer model that includes multiple physical parameters to better describe the observed thermal behaviour in pulsed thermographic inspection. Numerical simulations are used to evaluate the performance of the proposed method against four selected state-of-the-art methods. Results show that the accuracy of depth measurement has been improved up to 10% when noise level is high and thermal wave reflection coefficients is low. The feasibility of the proposed method in real data is also validated through a case study on characterising flat-bottom holes in carbon fibre reinforced polymer (CFRP) laminates which has a wide application in various sectors of industry.
... Based on a theoretical one-dimensional solution of pulsed thermography, [59] analyzed the depth predicting principle and procedure of four representative methods for the non-air interface situation, and compared with experimental results of one machined steel sample with eight flatbottom holes. The results indicate that Peak slope time (PST), Absolute peak slope time (APST) and Logarithmic peak second-derivative (LPSD) methods can give accurate defect depth for all kinds of sample-defect interface. ...
... The results indicate that Peak slope time (PST), Absolute peak slope time (APST) and Logarithmic peak second-derivative (LPSD) methods can give accurate defect depth for all kinds of sample-defect interface. However, the Peak contrast time (PCT) method is easily affected by defect size, sample-defect interface [59]. On the other hand Zeng et al. [60] propose a new method for defect depth prediction. ...
This paper presents a procedure for detecting and quantifying defects in reinforced concrete structures by using the method of active infrared thermography (IRT). For quantitative analysis, a methodology of thermal stimulation of concrete specimens and post-processing of the gathered data was developed. Presented methodology uses principles of step heating (SH) thermography, pulsed phase (PPT) thermography, principal component thermography (PCT) and correlation operators technique. A short descriptions of the post-processing methods used in the research is also provided in the paper. All three post-processing methods i.e. PPT, PCT and correlation operators technique have shown the possibility to enhance the defect detection in concrete structures in comparison to raw thermograms. According to the data accessible to the authors, in presented research, correlation operators and PCT post-processing techniques are being successfully used for the first time for defect detection within concrete structures. The results of the research clearly show the possibility of using active IRT for the detection and assessment of defect depth (quantification) in reinforced concrete structures with the measurement error within 10%.
... Instead of only dealing with lateral defect quantification or defect-depth quantification, several researchers are working on both lateral defect quantification and defect depth quantification using optical thermography. Wei et al. [134] enhanced defect-depth estimation in pulsed thermography by introducing a normalization factor N that accounts for defect size (p = D/d) and material thickness (v = l/d), addressing the limitations of the classical peak slope time (PST) method [135]. The classical PST approach assumes one-dimensional heat conduction, leading to depth-estimation errors, particularly for large defects or thick materials. ...
Quantifying defects in carbon-fiber-reinforced polymer (CFRP) composites is crucial for ensuring quality control and structural integrity. Among non-destructive evaluation techniques, thermography has emerged as a promising solution for defect detection and characterization. This literature review synthesizes current advancements in active thermography methods, with a particular focus on vibrothermography and optical thermography, in identifying defects such as delaminations and barely visible impact damage (BVID) in CFRP composites. The review evaluates state-of-the-art techniques, highlighting the advanced applications of optical thermography. It identifies a critical research gap in the integration of vibrothermography with advanced image-processing methods, such as computer vision, which is more commonly applied in optical thermography. Addressing this gap holds significant potential to enhance defect quantification accuracy, improve maintenance practices, and ensure the safety of composite structures.
... Some of the common SCT features used for defects depth evolution are listed in Table 9.4, and readers can find more information regarding each of these methods in [81] and [82]. ...
The adhesively bonded joints have become of paramount significance due to
their numerous advantages. Nevertheless, their application has been limited by
a lack of adequate nondestructive evaluation (NDE) techniques to determine the
state of damage within such joints and to monitor their structural integrity. The
objective of this chapter is a comprehensive review of investigations and efforts to
inspect the integrity of adhesive joints using novel NDE and condition monitoring
techniques. Each section of this chapter is dedicated to summarize contributions
on application of a certain NDE method. These methods include, Acoustic
Emission, IR Thermography, Electrical Impedance, Digital Image Correlation and Ultrasonic.
... Some of the common SCT features used for defects depth evolution are listed in Table 9.4, and readers can find more information regarding each of these methods in [81] and [82]. ...
... To this end, Zhu et al. [30] proposed a temperature integral method to determine a profile line that best estimates the defect size. On the other hand, based on 1D heat conduction theory, closed form solutions of thermal response were available [31][32][33], which were direct and fast for defect sizing. But their performance depends on the size and depth of the defect. ...
Active infrared thermography is proved to be viable and attractive for non-destructive evaluation of interfacial defects like delaminations in a coating-substrate system. But it is a challenging task to accurately quantify small and deeply buried defects from thermal images, due to the inevitable effects of lateral heat diffusion and measurement noise.
The aim of this work is to estimate the size and pattern of defects at the interface of a two-layer system with high accuracy and high reliability based on step heating thermography.
To characterize the effect of defect on the heat flow, a virtual heat flux is assumed at the interface, which is reconstructed from measured surface temperature by solving a three-dimensional inverse problem. The inverse solution is obtained using the Green’s function and regularization techniques, and then used for estimating the defect pattern by threshold segmentation. An improvement on computational efficiency is achieved by an iteratively substitution of nodal temperature.
Simulations with synthetic data generated by a finite element model validate the feasibility of this approach. Results obtained from experiments for an Aluminum oxide/steel system show the robustness of this approach, when temperatures are contaminated with measurement noise. Both the performance on estimation of various defect shapes and the effects of regularization are discussed.
This study show that the present approach brings an improvement in accuracy and reliability for the estimation of size and pattern of defects with various diameter-to-depth ratios, in comparison with conventional techniques.
... For example, Badghaish and Fleming used step-heating IR thermography to detect internal damage in FRP materials by applying heat to the material for a short period of time using optical heaters [38]. IR thermography currently uses high power excitation sources (e.g., flash lamps) to illuminate the sample on its surface and generate heat to detect cracks in the bulk material [39][40][41][42][43][44]. However, major problems arise when the defect is too deep to be reached by a significant amount of heat, so that the use of external thermal sources may limit the detection of defects only within a few millimetres from the material surface. ...
The through-the-thickness reinforcement of carbon-epoxy composite joints with shape memory alloy (SMA) tufts has shown significant improvement of the mechanical strength, fracture toughness, and delamination resistance. This study explores the thermal-electric properties of SMA filaments tufted in composite T-joints to exhibit multiple functionalities including material-enabled thermographic inspection and structural health monitoring via in-situ strain sensing. Infrared thermography image analysis was performed on both pristine and damaged T-joint specimens subject to pull-off testing. Experimental results showed that the heat generated by SMA tufts measured by an infrared camera provided accurate indication of delamination perpendicular to the tuft direction. SMA tufts were also used as strain sensors embedded within the T-joint. Local changes of the electrical resistance in SMA filaments, both separately and within the joint, were observed during pulling loads. Digital Image Correlation measurements exhibited good correlation between electrical resistance variations and the opening of delamination. These results pave the way for the development of multifunctional composite joining systems combining enhanced through-the-thickness damage tolerance and self-sensing capabilities.
... Various works have also approached the modeling of this problem in a more complex way, such as: 2D analytical model [22], 3D analytical model [23], finite differences method (FDM) [1], finite volume method (FVM) [24], and finite elements method (FEM) [25]. In the same context, [26,27] propose modeling approach based on the quadrupole method [28], which are particularly well suited to multilayers such as those encountered in this type of problem. ...
... Defects of 45 × 45 mm could be considered as being infinite if the sample thickness is less than a few millimeters. It is worth reiterating that the temperature signals over defects are independent of the defect lateral dimensions if they exceed the defect depth by more than 5-10 times [29,30]. ...
The principle of Line Scan Thermography (LST) was used to develop a self-propelled infrared thermographic nondestructive testing device for the inspection of large, relatively flat composite aerospace parts, such as aircraft wings. The design of the unit allowed the suppression of noise from reflected radiation. The new equipment, using the LST method, provided defect detectability similar to that achieved with a classic, static, flash heating procedure, but with a higher rate of testing. Also, the line heating principle ensured more uniform thermal patterns, and the proper choice of scan speed and field of view allows the selection of optimal time delays and the creation of maps of defects at different depths. Defect characterization efficiency was improved by using a trained neural network.
... However, this work still lacks a general criterion to determine the cut-offs of phase contrast profiles for different cases. In addition, closed form solutions of thermal response and corresponding derivatives are available for the PT [29] and SHT [16,30], but they are only valid in 1-D case. For in-plane defects with finite lateral dimensions, the 2-D or 3-D heat conduction is encountered around the defect [31][32][33]. ...
Step heating thermography is a non-destructive testing (NDT) technique that inspects interior defects by observing surface temperature rises during a long pulse heat stimulation. Due to the heat diffusion induced blurring of defect shapes, it is a challenging task to accurately determine the sizes of deep and small defects. This work focuses on estimating the size of a subsurface defect by an inversion of temperature images for the step heating thermography, to overcome the information loss during the propagation of thermal waves. We assume a space- and time-dependent virtual heat flux on the defect surface, which is reconstructed from surface temperature measurements by solving a two-dimensional inverse heat conduction problem. The local future time concept is combined with the Tikhonov's regularization to stabilize the inverse solution. A prudent choice of the regularization parameter is carried out through the L-curve. The feasibility of the proposed approach is assessed by numerical simulations and experiments. It is shown that the inversion brings an improvement in defect sizing accuracy for defects with low width-to-depth ratios and an efficient suppression of measurement noises.
... Zeng et al. [15,16], proposed to first multiply both sides of Equation (2) with √ t, and define a new time-dependent function f (t) as ...
Pulsed thermography has been used significantly over the years to detect near and sub-surface damage in both metals and composites. Where most of the research has been in either improving the detectability and/or its applicability to specific parts and scenarios, efforts to analyse and establish the level of uncertainty in the measurements have been very limited. This paper presents the analysis of multiple uncertainties associated with thermographic measurements under multiple scenarios such as the choice of post-processing algorithms; multiple flash power settings; and repeat tests on four materials, i.e., aluminium, steel, carbon-fibre reinforced plastics (CFRP) and glass-fibre reinforced plastics (GFRP). Thermal diffusivity measurement has been used as the parameter to determine the uncertainty associated with all the above categories. The results have been computed and represented in the form of a relative standard deviation (RSD) ratio in all cases, where the RSD is the ratio of standard deviation to the mean. The results clearly indicate that the thermal diffusivity measurements show a large RSD due to the post-processing algorithms in the case of steel and a large variability when it comes to assessing the GFRP laminates.
... Quantitative evaluation is a research focus in the field of NDE. Defect information can be detected by peak temperature, peak time, and temperature information at a single moment [10]. Another way to approach defect evaluation is to use deep learning. ...
Active infrared thermography (AIRT) is a significant defect detection and evaluation method in the field of non-destructive testing, on account of the fact that it promptly provides visual information and that the results could be used for quantitative research of defects. At present, the quantitative evaluation of defects is an urgent problem to be solved in this field. In this work, a defect depth recognition method based on gated recurrent unit (GRU) networks is proposed to solve the problem of insufficient accuracy in defect depth recognition. AIRT is applied to obtain the raw thermal sequences of the surface temperature field distribution of the defect specimen. Before training the GRU model, principal component analysis (PCA) is used to reduce the dimension and to eliminate the correlation of the raw datasets. Then, the GRU model is employed to automatically recognize the depth of the defect. The defect depth recognition performance of the proposed method is evaluated through an experiment on polymethyl methacrylate (PMMA) with flat bottom holes. The results indicate that the PCA-processed datasets outperform the raw temperature datasets in model learning when assessing defect depth characteristics. A comparison with the BP network shows that the proposed method has better performance in defect depth recognition.
... Since ΔT is a function of time, which increases if heat conduction is hindered at a defect, the 1st derivative of ΔT appears a maximal peak at this moment. The time duration, the SCT t m , is evident in calculating the depth of the defect [21,22], ...
The determination of defect depth is one of the important advantages of pulsed thermography. The existing methods for depth estimation in pulsed thermography are generally established based on the one-dimension heat conduction along the thickness of the sample. However, most of the methods neglect the effects of defect size and sample thickness, which induces additional systematic errors in depth estimation. In this study, simulations are conducted to demonstrate that the accuracy of depth determination of defects is greatly influenced by the defect size and sample thickness in some simulations. By establishing the relationship between the characteristic time and these factors, an accurate depth determination method based on the peak slope time is proposed. The proposed method has been applied to characterize the defect depths of a composite panel with flat-bottomed holes. The experimental results show that the use of the proposed method is able to identify the depths of defects with high accuracy.
... A. Vageswar et al. [56] investigated the peak contrast slope method using PT in transmission mode to estimate the depth of FBH defects in steel structures. Z. Zeng et al. [57] used PT to investigate the steel sample with FBH defects filled with different materials to replicate different non-air interfaces. The comparison between peak slope time method, absolute peak slope time method, logarithmic peak second-derivative method, and peak contrast time method showed that the later one is extremely influenced by defect size and interface while the other three techniques provided accurate defect depth. ...
This study performed an experimental investigation on pulsed thermography to detect internal defects, the major degradation phenomena in several structures of the secondary systems in nuclear power plants as well as industrial pipelines. The material losses due to wall thinning were simulated by drilling flat-bottomed holes (FBH) on the steel plate. FBH of different sizes in varying depths were considered to evaluate the detection capability of the proposed technique. A short and high energy light pulse was deposited on a sample surface, and an infrared camera was used to analyze the effect of the applied heat flux. The three most established signal processing techniques of thermography, namely thermal signal reconstruction (TSR), pulsed phase thermography (PPT), and principal component thermography (PCT), have been applied to raw thermal images. Then, the performance of each technique was evaluated concerning enhanced defect detectability and signal to noise ratio (SNR). The results revealed that TSR enhanced the defect detectability, detecting the maximum number of defects, PPT provided the highest SNR, especially for the deeper defects, and PCT provided the highest SNR for the shallower defects.
... OPT is the process of using a pulsed heat source as the external source to analyze the specimen. It is used in many applications due to its pulse and good inspection efficiency [7][8][9]. ...
With the increasing use of carbon fiber reinforce polymer (CFRP) in the aerospace industry, it has become necessary to monitor its quality. During the manufacture and service process defects such as debonds which are subsurface occur in the specimen. Generally, optical pulsed thermography (OPT) non-destructive testing (NDT) is used to detect these defects. However, the current techniques and algorithms still suffer from the background noise and poor resolution. In this paper, wavelet domain based image denoising and defect detection algorithm is proposed using the principal component analysis (PCA). Then wavelet domain based Gaussian low pass filtering (GLP) and enhancement approach is applied to remove the noise and extract the defect information. The proposed algorithm is tested on two different CFRP specimen and results are evaluated on an event based F-score. The results indicate that the proposed algorithm is able to remove the noise and extract the defects comprehensively.
... As discussed in Section.4.2, the delamination ranging from 0.46 mm to 2.30 mm of depth can be visualized by enhanced thermal pattern method based on the impulse response. Moreover, to determine the delamination depth, the phase contrast between defected and non-defected areas can be exploited, by comparison of the obtained impulse responses based on PT theory [58]. The defected areas are detected and selected by K-PCA as shown in Fig. 14 in line with the sample introduction in Fig. 8. ...
The growing application of composite materials in aerospace leads to the urgent need of non-destructive testing and evaluation (NDT&E) techniques capable of detecting defects such as impact damage and delamination possibly existing in those materials. Eddy current pulsed thermography is an emerging non-destructive testing (NDT) technique capable of detecting such defects. However, characterization of delamination within composite materials is difficult to be achieved by a single pulse excitation, especially in carbon fiber reinforced plastic materials as the extraction of thermal diffusion in such multi-layered structures is challenging. To cope with this problem of signal-to-noise ratio, this paper proposes the eddy current pulse-compression thermography (ECPuCT), combining the Barker code modulated eddy current excitation and pulse-compression technique to enhance the capability of characterizing delamination on carbon fiber reinforced plastic materials. Additionally, a thermal pattern enhanced method based on kernel principal component analysis technique is used to locate the delaminated areas. Two features, including a newly proposed crossing point of impulse responses related to defective and non-defective areas and skewness of impulse responses are investigated for delamination depth evaluation. Results show that delamination can be detected within depths ranging from 0.46 mm to 2.30 mm and both the proposed features have a monotonic relationship with delamination depths.
... The idea behind the determination of these time points is based on the fact that, when studying the heat diffusion into the material bulk after the application of a thermal pulse, the time taken for the thermal wave to be reflected back to the surface is inversely proportional to the thermal diffusivity of the material and directly proportional to the square of its depth [6]. The first proposed and the most commonly used method utilises the time point when the maximum thermal contrast between a defective and a preselected reference point occurs, known as Peak Contrast Time [25][26][27]. Even though this informative parameter can produce quantitative depth information, one of its major limitations is the fact that the peak contrast appears relatively late, when the 3D heat diffusion around the defect has a great influence on the acquired result. ...
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The present study intends to show the potentiality of pulsed thermographic imaging to quantitatively characterise hidden defects in Carbon Fibre Reinforced Polymers. By comparing the performance of different depth retrieval procedures, it was possible to evaluate the produced depth estimation accuracy and to define the impact of different experimental and analysis parameters in quantitative analysis.
Abstract
In the present study, a Carbon Fibre Reinforced Polymer (CFRP) sample of trapezoid shape, consisting of internal artificial delaminations of various sizes and depth locations, is investigated by means of optical pulsed thermography for the retrieval of quantitative depth information. The main objectives of this work are to evaluate the produced depth estimation accuracy from two contrast-based depth inversion procedures as well as to correlate the acquired results with characteristics such as the location and size of the detected features and with analysis parameters such as the selection of the sound area. Quantitative analysis is performed in both the temporal and frequency domains, utilising, respectively, the informative parameters of thermal contrast peak slope time and blind frequency. The two depth retrieval procedures are applied for the depth estimation of features ranging in size from 3 mm to 15 mm and in depth from 0.2 mm to 1 mm. The results of the present study showed that the two different analyses provided efficient depth estimations, with frequency domain analysis presenting a greater accuracy. Nevertheless, predicting errors were observed in both cases and the factors responsible for these errors are defined and discussed.
... This method actually measures the thickness distribution of a blade sample, which is used for a quantitative analysis for the adhesive quality. Although thickness measurement has been commonly performed using pulsed thermography [15][16][17][18], it however can only supply limited power for thermal excitation that is not sufficient for a reliable measurement for thick materials. Our method instead uses a step heating that can provide more energy by extending the heating time. ...
The wind turbine blade is one of the most important parts in a wind turbine system. The blade consists of a massive outer shell that is supported by an internal shear web with a thick layer of adhesive between them. Therefore the adhesive quality is a critical factor to guarantee it works properly for a designed service life of up to two decades. At present, it has been very challenging to evaluate the quality of this adhesive layer. In this study, a step-heating transmission thermography method was developed to measure the thickness variation of a blade shell, which was used for a quantitative evaluation of the adhesive quality. This method was verified first in a laboratory using three simulated blade specimens with wall thicknesses ranging from 13 to 31 mm. It was then used to inspect a 45.3 m wind blade. Based on the measured thickness distributions, an automated searching algorithm was developed to locate the adhesive edges which in turn determined the adhesive width and the adhesive-deficient area. The results obtained in this research demonstrated that the transmission thermography thickness measurement method is an effective way to evaluate the adhesive quality for wind turbine blades.
... The methods reported in literature for this purpose can be distinguished in empirical and experimental. The main techniques were reviewed and contrasted by [12,13], who used samples with flat-bottom holes as simulated defects in their experiments. Experimental studies [14] have showed that delaminations with a ratio of diameter to depth of the delamination less than 0.5 cannot be detected using thermography. ...
The use of pulsed thermography as a non-destructive evaluation tool for damage monitoring of composite materials has dramatically increased in the past decade. Typically, optical flashes are used as external heating sources, which may cause poor defect definition especially for thicker materials or multiple delaminations. SMArt thermography is a new alternative to standard pulsed thermography as it overcomes the limitations on the use of external thermal sources. Such a novel technology enables a built-in, fast and in-depth assessment of both surface and internal material defects by embedding shape memory alloy wires in traditional carbon fibre reinforced composite laminates. However, a theoretical model of thermal wave propagation for SMArt thermography, especially in the presence of internal structural defects, is needed to better interpret the observations/data measured during the experiments. The objective of this paper was to develop an analytical model for SMArt thermography to predict the depth of flaws/damage within composite materials based on experimental data. This model can also be used to predict the temperature contrast on the surface of the laminate, accounting for defect depth, size and opening, thermal properties of material and defect filler, thickness of the component, and intensity of the excitation energy. The results showed that the analytical model gives good predictions compared to experimental data. This paper is one of the first pioneering work showing the use thermography as a quantitative non-destructive tool where defect size and depth could be assessed with good accuracy.
Thermal wave radar is one of the active infrared thermographic techniques that detects defects by applying a broadband frequency modulated excitation and cross-correlation. Although it outperforms conventional methods in the depth resolvability and defect detectability, there still exist difficulties in the estimation of defect depth due to the distortion effect of heat diffusion and noises. This work aims to estimate the depth of an internal defect using a new parameter instead of the widely used blind frequency, namely the sensitive frequency, at which a maximum phase contrast is reached. The thermal wave radar is implemented by using a linear frequency modulated laser excitation. The phase contrast in function of frequency is obtained from the dual orthogonal demodulation algorithm. A linear relationship with calibrated coefficients is established between the sensitive frequency and the reciprocal of the square of depth. The effect of defect size on the linear relationship is studied, and a correction of the linear relationship is proposed to improve the accuracy of depth estimation. The proposed method is numerically verified and experimentally validated, and the results illustrated that the depths of defects with various aspect ratios can be well estimated.
In this paper, the modulated step-heating thermography is proposed for opaque coating thickness measurement. The surface is heated by a modulated heating flux at a frequency that the thermal wave is confined within the coating layer. The DC component of the thermal signal is normalized by the amplitude of the AC component to cancel out the influences from the variations in heating intensity, surface absorptivity and emissivity, resulting in a linear correlation to the coating thickness. Meanwhile, it eliminates the need for tedious frequency trail and the issue of the nonmonotonicity as suffered in conventional thermography. Both theoretical and experimental results confirmed the effectiveness. Specimens with thickness ranging from 100~400 μm are measured with a relative error within ±7.9%.
Infrared thermography (IRT) aims at the detection of surface or subsurface features of composite materials (e.g., fiber misalignments, voids, slag inclusions, etc.), based on temperature differences on the test surface during the monitoring by an IR camera even when only one side of the test structure is accessible. IRT technique is viewed as one of the most valuable NDT tools for online control and structural health monitoring of the materials and structures operating in environments with different levels of mechanical stress levels, thanks to its ability to provide a quick online appraisal of the health status of the test structures, thus avoiding the waste of time that would otherwise be spent when conducting the back-and-forth testing to investigate the performance of newly installed structures or designed materials under impact loading (i.e., reliability test). In addition, IRT is also capable of detecting several types of damage and/or material degradation effects (e.g., impact damage, delamination, disbonds, holes, corner splits, etc.) that occur during the material’s service life. IRT instruments are generally easy to operate and the fact that they can provide useful information for the material characterization that can be evaluated through the visualization of impact-induced thermal signals, specifically when analyzing the initiation and propagation of the impact damage, is another added advantage. Additionally, IRT techniques present several advantages, which include greater inspection speed, higher resolution/sensitivity, as well as the accurate and fast detection capabilities of the material or test structure inner defects/damage due to heat conduction and require no couplants. In this context, IRT can be used to test nearly all kinds of fiber-reinforced composite material and structural systems without fear of contamination by the test systems. However, there is little expectation of its successful application to thick sections, other than for sandwich panels enclosing significantly high levels of water content, or large voids, and the probable need of an active through-the-thickness heat source. In addition, the technological progress with the continued release of new and more sophisticated IR thermographic devices, more ergonomic, lighter, and user-friendly would pave the way to possible new applications, which equally requires a continued upgrading of procedures and data analysis methods.
Among the Non-Destructive Testing (NDT) techniques available today, Active Infrared Thermal Testing (AIRTT) is certainly one of the most flexible and promising. The goal of this work was to compare the results obtained with a common Lock-in Thermal Test (LTT) and the same test using a true sinusoidal stimulation obtained through a closed-loop controller. The results showed a poor dynamic response of the common system and a lack of proportionality between the reference signal and the generated optical stimulation. To improve its response, it was implemented a PID controller using a light sensor to close the feedback loop. The amplitude images obtained with this controller showed a significant improvement in the results. Defects invisible with the common LTT were now identifiable. The phase images obtained using the controller with feedback revealed higher sensitivity with lower noise. Despite only one system was tested, the results show that the optical stimulation used in LTT is not very accurate and can/should be improved and, that a sensitivity 2.5 times higher than the common LTT was achieved with a real sinusoidal stimulation.
Abbreviation: NDT: Non-Destructive Tests; AIRTT: Active Infrared Thermal Testing; LTT: Lock-in Thermal Test; cLTT: common LTT; PID: Proportional, Integral and Derivative; CFRP: Carbon Fibre Reinforced Polymers; TTT: Transient Thermal Tests; LDR: light-dependent resistor; PMMA: Poly(methyl methacrylate)
Defects and damage during the manufacture of composites or metal parts are inevitable. Therefore, non-destructive testing is essential to prevent failure and increase the reliability of composite structures or metal components. Non-destructive thermography technologies have shown many advantages in this regard. In the thermography technology, the temperature variation of the external surface of the work piece was determined by receiving the radiated infrared waves. These waves indicated the point temperature precisely. In this paper, a compelet and comprehensive study of non-destructive infrared thermgraphy test methods for metal and composite inspection, detailed analysis was performed and the developments of infrared therapeutic technologies were investigated. First, the basic concepts for non-destructive test thermography were introduced. Then different types of thermography with radiation stimulation are described and compared. In the following, research examples of the application of thermography methods and some of the strengths and limitations of thermography technologies were compared and described in detail.
Pulse thermography is used in various industries to inspect and monitor certain parts and assemblies. Corrosion in steel structures and components is one of the most important defects that impose huge costs on industries each year, which can be partially reduced by timely detection. There are many ways to diagnose corrosion, but the high speed of testing, the need to not sample, the inspection of large surfaces in low time, and the ability to perform it on many materials, are the advantages of pulse thermography. In this paper, from non-destructive testing methods, pulsed thermography is used to detect corrosion defects in metal sheets. The samples tested in this paper are made of low carbon steel and alloy steel which have many applications in various industries. The aim of this study was to simulate and identify corrosion defects in steel parts. Various defects were designed and fabricated to evaluate the strength of this non-destructive testing in determining the minimum diameter and maximum depth. The effects of excitation sources distance, radiation angle, material of samples and duration of excitation on the tests were investigated. The ability to detect defects without the need for image processing has been exploited to the advantage of the employed method. From the pattern of defects created in the samples, the smallest detected defect in the low carbon steel specimen was 4 mm in diameter at 1 mm depth and in the alloy steel specimen the smallest detected defect was 3 mm in diameter at 1 mm depth.
The carbon fiber reinforced polymer (CFRP) has been widely used in the aerospace field. During its utilization under the severe environment, CFRP is prone to defects, including impacts, debonds, delaminations, and cracks. Optical pulsed thermography (OPT) nondestructive testing has been used for qualitative and quantitative analysis of such defects. This paper proposes the nonlinear transfer model of peak contrast time analysis to determine defect depth by using OPT technology. The mechanism of the nonlinear relationship between peak contrast time and defect depth is demonstrated and validated by experiments. To effectively predict the defect depth, gaussianization transform is modeled as a nonlinear conversion in defects depth determination. The results of the experiments have indicated that the proposed method has significantly enhanced the accuracy in depth determination.
Methods in infrared nondestructive testing such as normalized thermal contrast (NTC) and thermal signal reconstruction (TSR) are based on a pixel-by-pixel time domain analysis that ignores spatial correlation. Other techniques in the frequency domain such as pulsed phase thermography (PPT) present the same disadvantage. In this paper, we propose a method to evaluate defects in composite specimens based on image decomposition into a 2D orthogonal space. We compare NTC, TSR, PPT, and principal component thermography (PCT) with the new approach by inspecting three samples of composite anisotropic materials. Without defining a sound area our method estimates the depths of defects up to 1.2 mm in carbon and glass reinforced plastic specimens. An implementation of the proposed method in Matlab is available at https://github.com/charlielito/2DOrthogonal_Polynomial_Decomposition.
In the previous chapter thermography has been shown to have potential for the identification of defects in adhesive bonds. The current chapter will initially provide an in depth review of the main types of thermography that use the addition of energy from light sources, namely pulsed, lock-in and pulse phase thermography. The types of detectors that may be used for these techniques are then considered. The underpinning physics of heat transfer that enables the detection of defects using thermography are then introduced before interpretation of the thermal data to extract estimated defect size is discussed. The practicalities of experimentation using thermography are then introduced including the experimental setup. Software and data collection and processing methods used in the current work are introduced and the importance of various variables studied. From this investigation knowledge of the importance of the experimental parameters is obtained and used in the remainder of experimental work.
This paper proposes to use minus peak time of second derivative with respect to time on logarithmic curve of temperature versus time as a characteristic time for defect depth prediction in pulsed wave thermography. First, the paper introduces the basic principle of pulsed wave thermography, and constructs the theoretical relation between logarithmic minus peak second derivative time and the square of defect depth based on the solution of semi-infinite body. Then, two specimens of steel and aluminum were manufactured with flat-bottom holes to simulate defects. Thermographic image sequences of those two specimens were obtained by using pulsed wave thermography, and then the logarithmic minus peak second derivative time were extracted. The extracted characteristic time has a very good linearity relation with the square of defect depth, and this linearity could be used for defect depth prediction in practical applications. The advantages and disadvantages of the proposed method and the widely used logarithmic peak second derivative method are discussed.
The principles, limitations, and potential complications of thermography technology are examined when applied to the nondestructive testing (NDT) of composites. The introduction of infrared cameras eliminated the need for temperature-sensitive pigments or scanning apparatus for remote temperature sensing applications. Polymer composites have relatively low thermal effusivities and provide strong infrared signals that are above the level of background infrared radiation and instrumentation noise. Induction or microwave excitation is appropriate for samples having some metallic content, but not for samples that are dielectric such as glass fiber reinforced polymeric composites. Changes in the surface temperature are detected in theromograpic practice by an infrared camera. Optical excitation uses visible light to heat the surface to offer noncontact, wide-area performance that is comparable to the performance offered by ultrasonic testing.
In this paper a novel approach is proposed which combines simultaneously advantages both of pulse (PT) and modulated (MT) infrared thermography. In a nondestructive evaluation perspective, the specimen is pulse-heated as in PT and the mix of frequencies of the thermal waves launched into the specimen are unscrambled by performing the Fourier transform of the temperature evolution over the field of view. Of interest is the maximum phase image with many attractive features: deeper probing, less influence of surface infrared and optical characteristics, rapid image recording (pulse heating, surface -wide inspection), possibility to inspect high thermal conductivity specimens. Several results are presented and the theory is discussed as well. - 2 - 1. Introduction Infrared thermography (IT) is a nondestructive evaluation (NDE) method with an increasing span of applications 1,2,3 . To summarize briefly the principle of operation, in the active scheme, an external thermal stimulation is...
In the last few years, several quantitative inversion methods have been proposed to analyze pulsed phase thermographic data: statistical methods [1], Neural Networks [2] and wavelets [3], with a wide range of reported accuracies. In the present paper a new approach is proposed based on absolute phase contrast computations defined in a similar way as for absolute temperature contrast [4]. Phase contrast data is then used to estimate the blind frequency, i.e. the frequency at which the defect becomes visible for the 'first' time [5]. It was found an excellent agreement between defect depth z, and the corresponding blind frequencies f b . Experimental tests on Plexiglas ® and aluminum specimens demonstrate the potential of the technique on retrieving the depth of flat-bottomed holes. We also discuss temporal aliasing and its relationship with the phase delay images. As will be stressed, the unavoidable differences between the Continuous and the Discrete Fourier Transform of a time-dependent temperature decay signal can be effectively minimized not only by selecting a sampling frequency rate according to Shannon's Sampling Theorem (as is well-known [6]), but also by choosing an appropriate truncation window size [7].
Stimulated Infrared Thermography (TIS) is a fast and global method for NonDestructive Evaluation (NDE). Among the recently emerging NDE methods, it is probably the less intrusive one since it really needs no contact at all with the tested structure. A new inversion technique, using an early detection of the contrast, is presented to demonstrate how it recovers the depth of the defects with accuracy and partially removes the effects produced by the lateral heat diffusion.
Overview of nondestructive evaluation (NDE) using infrared thermography theoretical aspects experimental apparatus external thermal stimulation - methods and image processing internal thermal stimulation - methods and image processing quantitative analysis of delaminations inspection of materials with low emissivity by thermal transfer imaging thermal diffusity measurements of materials thermal tomography thermal NDE of nonplanar surfaces applications of infrared thermography to high temperatures.
We describe the early time behavior of reflected thermal wave pulses from planar subsurface scatterers, and describe methods for making depth images, independently of the lateral size of the scatterer.
Objective: To search for sesquiterpene components with structural diversity from Laurencia tristicha to supply for pharmacological activity screen. Methods: Compounds were isolated by means of column chromatography over normal phase silica gel and Sephadex LH-20, recrystallization, and HPLC. Structures were identified by spectroscopic methods including 1D and 2D NMR, IR, X-ray, and MS. Cytotoxicities of the purified compounds were evaluated by MTT method. Results: Five sesquiterpenes, aplysin (I), aplysinol (II), debromoaplysinol (III), laurebiphenyl (IV), and johnstonol (V) have been isolated and identified. In the cytotoxic assay compound IV was active against human cancer cell lines, HCT-8, Bel-7402, BGc-823, A549, and HeLa with IC 50 values of 1.77, 1.91, 1.22, 1.68, and 1.61 μg/mL, respectively. Compound III showed cytotoxicity against HeLa with IC 50 value of 3.6 μg/mL while other compounds were inactive (IC 50>10 μg/mL). Conclusion: Compounds I-V are isolated from L. tristicha for the first time. Compound III shows moderate selective cytotoxicity against HeLa cell line and compound IV is cytotoxicity against several human cancer cell lines.
We describe advances in the application of thermal wave imaging to NDI of disbonds and corrosion in aging aircraft. This technique uses an infrared (IR) video camera to image the surface of the aircraft after the application of a short pulse of heat. The heat is applied by high-power xenon flash lamps. The camera and flashlamps are connected to the control computer by a 50-ft cable. This design makes it highly portable, as well as suitable for robotic manipulation. The computer is used to process the digital video data stream from the IR camera, as well as to display the resulting images. The imaging requires only a few seconds per square foot of aircraft surface. The system is capable of detecting and measuring as little as 1% metal material loss. Disbonded metal-to-metal doublers are readily detected, and disbonds and delaminations in graphite and boron fiber composite structures can be imaged and their depths measured. Examples of disbonds as deep as 36 plies under a boron patch are presented, along with an example of discrimination of impact damage on a ply-by-ply basis in a carbon fiber composite.
The flash method including the single‐ and double‐ended method has gained widespread acceptance for measuring thermal diffusivity of thick foils (in millimeters) as well as thin films (in microns). However when the method is employed, some basic experimental conditions are assumed. In this paper, two of the assumptions, the finite absorption depth effect and the nonlinearity of the detector, are discussed in the situation of thin film samples. For the first one, the deviation of the factor ω1/2 (=π2αt1/2/L2) from 1.37 and the corresponding errors in deriving thermal diffusivity from t1/2 are discussed for various relative absorption depth δ. The result indicates criteria for the method to be available, that is, L≳10δ and L≳14δ for the double‐ and the single‐ended method. For the second one, by considering the errors in voltage output of a (Hg, Cd)Te IR detector, how the factor ω1/2 deviates from 1.37 and the corresponding errors in thermal diffusivity measurement under various initial temperature conditions are discussed. The results are shown graphically and tabulated.
Several methods have been reported in the literature using pulsed thermography for quantitative measurement of defect depth or sample thickness. In this paper, based on the analysis of a theoretical one-dimensional solution of pulsed thermography, we proposed to use the absolute peak slope time (APST) for quantitative measurement of defect depth. APST is the peak slope time of the curve which is obtained by multiplying the original temperature decay with the square root of the corresponding time. The theoretical model shows that APST has linear relation with square of defect depth, which was verified with the experimental results of an aluminum and a steel specimen with six flat-bottom wedges and holes as simulated defects respectively.
We describe the early time behavior of reflected thermal wave pulses, and relate that behavior to schemes for making depth images.
Pulsed thermography is an effective technique for quantitative prediction of defect depth within a specimen. Several methods have been reported in the literature. In this paper, using an analysis based on a theoretical one-dimensional solution of pulsed thermography, we analyzed four representative methods. We show that all of the methods are accurate and converge to the theoretical solution under ideal conditions. Three methods can be directly used to predict defect depth. However, because defect features that appear on the surface during a pulsed thermography test are always affected by three-dimensional heat conduction within the test specimen, the performance and accuracy of these methods differs for defects of various sizes and depths. This difference is demonstrated and evaluated from a set of pulsed thermography data obtained from a specimen with several flat-bottom holes as simulated defects.
Active thermography has gained broad acceptance as a non-destructive evaluation method for numerous in-service and manufacturing applications in the aerospace industry. However, because of the diffusive nature of the process, it is subject to blurring and degradation of the signal as one attempts to image deeper subsurface features. Despite this constraint, active thermographic response is deterministic, to the extent that the postexcitation time evolution for a defect-free sample can be accurately predicted using a simple one-dimensional model. In the patented thermal signal reconstruction method, the time history of every pixel in the field of view is compared to such a model in the logarithmic domain, where deviations from ideal behavior are readily identifiable. The process separates temporal and spatial nonuniformity noise components in the image sequence and significantly reduces temporal noise. Time-derivative images derived from the reconstructed data allow detection of subsurface defects at earlier times in the sequence than conventional contrast images, significantly reducing undesirable blurring effects and facilitating detection of low-thermal-contrast features that may not be detectable in the original data sequence. (C) 2003 Society of Photo-Optical Instrumentation Engineers.
Flash thermography is widely used to inspect Thermal Barrier Coatings (TBC) during manufacturing and maintenance for defects such as delamination or contamination. However, attempts to use thermography to quantify TBC thickness have been less successful. In conventional thermographic NDT applications, the sample surface is opaque to an incident light pulse, and highly emissive in the infrared. The situation is more complex in TBC's, as the coatings are translucent to visible light and near-IR radiation (including the IR component of the flash). Furthermore, TBC's are translucent to the mid-IR wavelengths at which many IR cameras operate. Thus, in the absolute worst case, the flash pulse does not heat the coating, and the camera does not see the coating. Although the latter problem can be mitigated by judicious choice of camera wavelength, it must also be recognized that both the heating and cooling mechanisms in a flash-heated TBC are different from the usual thermography model, where transit time of a heat pulse from the sample surface to a layer interface is an indicator of coating thickness. The resulting time sequence is processed using the Thermographic Signal Reconstruction to generate thickness maps which are accurate to an accuracy of a few percent of the actual coating thickness.
Thermal edge effects for crack-like defects have been calculated using the Wiener-Hopf technique. It is found that the crack surface temperature is reduced over a distance of a thermal diffusion length by heat flow around the crack edge to the cold underside of the crack. Surface thermal images have been computed for a straight-edged and a circular crack. Comparisons are presented of image profiles computed with and without inclusion of edge effects. Edge effects lead to the prediction that transient thermographic defect images should shrink with elapsed time. Experimental data are presented, which are in agreement with this prediction and demonstrate a simple means of defect sizing.
In this paper, a new absolute thermal contrast method is proposed for pulsed infrared thermography. It is based on the computations of reconstructed defect-free images so that no a priori knowledge of a sound area on the sample is necessary. Moreover, a correction is applied to take into account possible delays in the acquisition time. Results are presented both on Plexiglas TM and graphite-epoxy specimens. Comparisons with Pulsed Phase Thermography phase images are also presented along with a discussion on the advantages of the proposed method.
La Thermographie de Phase Pulsée (TPP) est une technique d'Évaluation Non-Destructive basée sur la Transformée de Fourier pouvant être considérée comme étant le lien entre la Thermographie Pulsée, pour laquelle l'acquisition de données est rapide, et la Thermographie Modulée, pour laquelle l'extraction de la profondeur est directe. Une nouvelle technique d'inversion de la profondeur reposant sur l'équation de la longueur de diffusion thermique : [mu]=([alpha] /[pi]f)1/2, est proposée. Le problème se résume alors à la détermination de la fréquence de borne fb, c à d, la fréquence à laquelle un défaut à une profondeur particulière présente un contraste de phase suffisant pour être détecté dans le spectre des fréquences. Cependant, les profils de température servant d'entrée en TPP, sont des signaux non-périodiques et non-limités en fréquence pour lesquels, des paramètres d'échantillonnage [delta majuscule]t, et de troncature w(t), doivent être soigneusement choisis lors du processus de discrétisation du signal. Une méthodologie à quatre étapes, basée sur la Dualité Temps-Fréquence de la Transformée de Fourier discrète, est proposée pour la détermination interactive de [delta majuscule]t et w(t), en fonction de la profondeur du défaut. Ainsi, pourvu que l'information thermique utilisée pour alimenter l'algorithme de TPP soit correctement échantillonnée et tronquée, une solution de la forme : z=C1[mu], peut être envisagée, où les valeurs expérimentales de C1 se situent typiquement entre 1.5 et 2. Bien que la détermination de fb ne soit pas possible dans le cas de données thermiques incorrectement échantillonnées, les profils de phase exhibent quoi qu'il en soit un comportement caractéristique qui peut être utilisé pour l'extraction de la profondeur. La fréquence de borne apparente f'b, peut être définie comme la fréquence de borne évaluée à un seuil de phase donné ?d et peut être utilisée en combinaison avec la définition de la phase pour une onde thermique : [phi]=z /[mu], et le diamètre normalisé Dn=D/z, pour arriver à une expression alternative. L'extraction de la profondeur dans ce cas nécessite d'une étape additionnelle pour récupérer la taille du défaut. Titre de l'écran-titre (visionné le 23 février 2006). Dans le résumé: le " 1/2 " de la formule "[mu]=([alpha] /[pi]f)1/2" est suscrit ; le " b " des symboles " fb " et " f'b "est souscrit ; le " 1 " de la formule " z=C1[mu] " et du symbole "C1" est souscrit ; le " n " de la formule " Dn=D/z " est souscrit. Thèse (Ph.D.)--Université Laval, 2005. Bibliogr. Disponible en formats XHTML et PDF
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